Estimation and Testing Under Sparsity: École d’Été de Probabilités de Saint-Flour XLV – 2015
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Starting with the popular Lasso method as its prime example, the book then extends to a broad family of estimation methods for high-dimensional data A theoretical basis for sparsity-inducing methods is provided, together with ways to build confidence intervals and tests The focus is on common features of methods for high-dimensional data and, as such, a potential starting point is given for the analysis of other methods not treated in the book
Starting with the popular Lasso method as its prime example, the book then extends to a broad family of estimation methods for high-dimensional data A theoretical basis for sparsity-inducing methods is provided, together with ways to build confidence intervals and tests The focus is on common features of methods for high-dimensional data and, as such, a potential starting point is given for the analysis of other methods not treated in the book
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